英文:
How to include both ends of a pandas date_range()
问题
以下是代码的中文翻译部分：
import pandas as pd
import datetime
# 选项 1
pd.date_range(datetime(2022, 1, 13), datetime(2022, 4, 5), freq='M', inclusive='both')
# 选项 2
pd.date_range("2022-01-13", "2022-04-05", freq='M', inclusive='both')
这两个选项返回的结果都是：DatetimeIndex(['2022-01-31', '2022-02-28', '2022-03-31'], dtype='datetime64[ns]', freq='M')。然而，我期望的结果是一个包含每个月份的日期的列表（4个日期），分别是 [一月, 二月, 三月, 四月]。
如果我们现在运行以下代码：
pd.date_range("2022-01-13", "2022-04-05", freq='M', inclusive='right')
我们仍然会得到与之前相同的结果。看起来 inclusive 对结果没有影响。
Pandas 版本：1.5.3
英文:
From a pair of dates, I would like to create a list of dates at monthly frequency, including the months of both dates indicated.
import pandas as pd
import datetime
# Option 1
pd.date_range(datetime(2022, 1, 13),datetime(2022, 4, 5), freq='M', inclusive='both')
# Option 2
pd.date_range("2022-01-13", "2022-04-05", freq='M', inclusive='both')
both return the list: DatetimeIndex(['2022-01-31', '2022-02-28', '2022-03-31'], dtype='datetime64[ns]', freq='M'). However, I am expecting the outcome with a list of dates (4 long) with one date for each month: [january, february, mars, april]
If now we run:
pd.date_range("2022-01-13", "2022-04-05", freq='M', inclusive='right')
we still obtain the same result as before. It looks like inclusive has no effect on the outcome.
Pandas version. 1.5.3
答案1
得分: 2
使用 MonthEnd 和 Day 偏移量
这是因为 2022-04-05 在你的月底日期（2022-04-30）之前。
你可以使用：
pd.date_range("2022-01-13", pd.Timestamp("2022-04-05")+pd.offsets.MonthEnd(),
freq='M', inclusive='both')
一个更健壮的变体，也能处理输入日期已经是月底的情况：
pd.date_range("2022-01-13",
pd.Timestamp("2022-04-05")-pd.offsets.Day()+pd.offsets.MonthEnd(),
freq='M', inclusive='both')
输出：
DatetimeIndex(['2022-01-31', '2022-02-28', '2022-03-31', '2022-04-30'],
dtype='datetime64[ns]', freq='M')
替代方法：使用 Period
pd.date_range(pd.Period('2022-01-13', 'M').to_timestamp(),
pd.Period('2022-04-30', 'M').to_timestamp(how='end'),
freq='M', inclusive='both')
中间结果：
pd.Period('2022-01-13', 'M').to_timestamp()
# Timestamp('2022-01-01 00:00:00')
pd.Period('2022-04-30', 'M').to_timestamp(how='end')
# Timestamp('2022-04-30 23:59:59.999999999')
或者作为周期：period_range
pd.period_range('2022-01-13', '2022-04-30', freq='M')
输出：
PeriodIndex(['2022-01', '2022-02', '2022-03', '2022-04'], dtype='period[M]')
英文:
using MonthEnd and Day offsets
This is because 2022-04-05 is before your month end (2022-04-30).
You can use:
pd.date_range("2022-01-13", pd.Timestamp("2022-04-05")+pd.offsets.MonthEnd(),
freq='M', inclusive='both')
A more robust variant to also handle the case in which the input date is already the month end:
pd.date_range("2022-01-13",
pd.Timestamp("2022-04-05")-pd.offsets.Day()+pd.offsets.MonthEnd(),
freq='M', inclusive='both')
Output:
DatetimeIndex(['2022-01-31', '2022-02-28', '2022-03-31', '2022-04-30'],
dtype='datetime64[ns]', freq='M')
alternative: using Period
pd.date_range(pd.Period('2022-01-13', 'M').to_timestamp(),
pd.Period('2022-04-30', 'M').to_timestamp(how='end'),
freq='M', inclusive='both')
Intermediates:
pd.Period('2022-01-13', 'M').to_timestamp()
# Timestamp('2022-01-01 00:00:00')
pd.Period('2022-04-30', 'M').to_timestamp(how='end')
# Timestamp('2022-04-30 23:59:59.999999999')
or as periods: period_range
pd.period_range('2022-01-13', '2022-04-30', freq='M')
Output:
PeriodIndex(['2022-01', '2022-02', '2022-03', '2022-04'], dtype='period[M]')
答案2
得分: 0
This is because the Month definition, if you use Day you see the difference.
When you count in months there is no effect.
For inclusive:
both: a <= x <= b (in math convention: [a, b])
neither: a < x < b (in math convention: ]a, b[)
right: a < x <= b (in math convention: ]a, b])
left: a <= x < b (in math convention: [a, b[)
You can't include beyond the limits
英文:
This is because the Month definition, if you use Day you see the difference.
When you count in months there is no effect.
For inclusive :
both : a <= x <= b (in math convention : [a, b])
neither : a < x < b (in math convention : ]a, b[)
right : a < x <= b (in math convention : ]a, b])
left : a <= x < b (in math convention : [a, b[)
You can't include beyond the limits
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